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Citation: Liu, S.; Lao, Q.; Zhou, X.; Jin,
G.; Chen, C.; Chen, F. Impacts of
Marine Heatwave Events on Three
Distinct Upwelling Systems and Their
Implications for Marine Ecosystems in
the Northwestern South China Sea.
Remote Sens. 2024,16, 131. https://
doi.org/10.3390/rs16010131
Academic Editor: Zhe-Wen Zheng
Received: 14 November 2023
Revised: 21 December 2023
Accepted: 26 December 2023
Published: 28 December 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
remote sensing
Article
Impacts of Marine Heatwave Events on Three Distinct
Upwelling Systems and Their Implications for Marine
Ecosystems in the Northwestern South China Sea
Sihai Liu 1,2, Qibin Lao 1,2, Xin Zhou 1,2, Guangzhe Jin 1,3,4, Chunqing Chen 1,2 and Fajin Chen 1,2,3,4,*
1College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China;
liusihai@stu.gdou.edu.cn (S.L.); qblao@stu.gdou.edu.cn (Q.L.); xinzhou@stu.edu.cn (X.Z.);
jingz@gdou.edu.cn (G.J.); 1112111002@stu.gdou.edu.cn (C.C.)
2School of Chemistry and Environment, Guangdong Ocean University, Zhanjiang 524088, China
3Key Laboratory for Coastal Ocean Variation and Disaster Prediction, Guangdong Ocean University,
Zhanjiang 524088, China
4
Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Sea of Department
of Education of Guangdong Province, Guangdong Ocean University, Zhanjiang 524088, China
*Correspondence: fjchen@gdou.edu.cn
Abstract: Under global warming, the frequency and intensity of marine heatwaves are increasing.
However, the inhibition of atmospheric-forcing marine heatwaves (AMHW) on upwelling and their
impacts on marine ecosystems remain poorly understood. To address this issue, the satellite sea surface
temperature and reanalysis data during 1998–2021 were analyzed in three distinct upwelling systems,
in the northwestern South China Sea. The results showed that the coastal tide-induced upwelling in
the west (W) of Hainan Island is primarily suppressed by enhanced stratification during the AMHW
events, since the coastal tide-induced upwelling is insensitive to wind weakening. Contrarily, the
wind-driven upwelling in the east (E) and northeast (NE) of Hainan Island are jointly regulated by wind
and stratification during the AMHW. Specifically, the AMHW events have a stronger inhibitory effect on
the upwelling and phytoplankton growth in the NE than that in the E. The causes could be the following:
(1) the background upwelling in the NE region is stronger than in the E; thus, the NE region has a higher
susceptibility to the wind weakening; (2) the wind-driven upwelling begins to be suppressed by AMHW
when the high-pressure system is aligned with the coastline of the upwelling. In the NE region, the
location of the high-pressure center during the occurrence of AMHW is positioned in closer proximity
to the upwelling area. Moreover, the inhibitory effect of wind weakening and stratification enhancing
on upwelling changes with the development of the AMHW. Before and during the mature phase of
AMHW, stratification and wind jointly inhibit upwelling and phytoplankton growth, while a shift to
stratification-dominated (>85%) occurs during the decline phase. This study suggests that MHW has a
great impact on the upwelling ecosystem, especially the wind-driven upwelling, which should be given
high attention under global warming (with increasing MHW events in the future).
Keywords: AMHW; upwelling; wind; stratification; Hainan Island
1. Introduction
Upwelling in the ocean is characterized by the ascending motion of seawater, exhibit-
ing velocities typically between approximately 10
−6
and 10
−4
m per second [
1
]. Coastal
upwelling is an important component of coastal ocean circulation and is critical for material
transport [2,3]. Coastal upwelling contributes over 10% of the global ocean’s new produc-
tivity [
4
] and nearly 20% of global fishing yields [
5
], despite its coverage area accounting for
only 1% of global ocean surface. Moreover, upwelling can bring deeper eutrophic water into
the upper layer, which can trigger the growth of phytoplankton, thereby changing a series
of biogeochemistry processes, such as carbon and nitrogen cycles [
6
]. Therefore, upwelling
plays an extremely important role in global marine ecology and climate change [7,8].
Remote Sens. 2024,16, 131. https://doi.org/10.3390/rs16010131 https://www.mdpi.com/journal/remotesensing
Remote Sens. 2024,16, 131 2 of 20
Marine heatwaves (MHW) are sustained anomalies in sea surface temperature (SST)that
exceed the climatological threshold and have severe impacts on marine ecosystems [
9
–
11
].
Substantial subtropical MHW are predominantly triggered by persistent atmospheric high-
pressure systems, which are linked to amplified solar radiation and unusually weak wind
speeds [
12
]. The close association among underlying atmospheric processes, MHW, and
upwelling accentuates the crucial need to study their impacts on upwelling and ecosystem
dynamics, particularly in the context of intensifying MHW. Some previous studies have
shown the role of upwelling in mitigating MHW, such as the fewer MHW days near major
eastern boundary upwelling systems than in open ocean regions [
13
,
14
]. However, the
impact of MHW on upwelling has been largely ignored [
15
–
17
]. In nutrient-limited tropical
and subtropical regions, the enhanced stratification resulting from marine heatwaves ulti-
mately leads to a reduction in surface availability of nutrients and Chl-aconcentration [
18
].
To date, the understanding of the extent and mechanism of the impact of MHW on different
distinct upwellings remains unclear.
The South China Sea (SCS) is a large semi-enclosed marginal sea basin situated at
the northwestern Pacific Ocean (99–125
◦
E, 0–25
◦
N). During the period 1982–2019, MHW
events in the SCS became more frequent, intense, widespread, and severe. According to
a diagnosis of synoptic-scale heat budgets, the extreme warming in the SCS is primarily
associated with near-surface anticyclonic anomalies, which often accompany the westward
extension of the Western Pacific Subtropical High [
19
,
20
]. Regarding the relationship
between MHW and upwelling in the SCS, previous studies have primarily emphasized the
decrease in Chl-aconcentrations during MHW periods in the Western SCS, attributed to
the weakening of upwelling [
21
], with limited research delving into the detailed process of
MHW inhibiting upwelling.
The SCS experiences upwelling-favorable southern winds during summer due to the
influence of the East Asian monsoon [
22
]. Hainan Island is situated on the northwestern
continental shelf of the SCS; there are three distinct upwellings around Hainan Island
(Figure 1). The upwellings in the eastern (E) and northeast (NE) regions of Hainan Island
are driven, respectively, by the southwest and southeast monsoons [
23
–
25
]. Furthermore,
Ekman pumping induced by wind stress curl is regarded as another crucial factor in
generating upwelling in E and NE regions [
26
], and even as the primary cause of interannual
variability in the upwelling of the E regions [
27
,
28
]. Variations in coastal topography
significantly contribute to the formation of upwelling centers distributed in the E and
NE regions [
1
]. In addition to wind, topography, ocean currents, eddies, and tides have
also been reported as significant factors influencing the upwelling in the northeastern
region [
23
,
29
,
30
]. On the contrary, the upwelling on the west (W) of Hainan Island is
mainly induced by stratification and tides [
24
,
31
,
32
]. Firstly, the W region is generated by
two factors. Firstly, stratification is formed in the upper layer of the middle area of the
Beibu Gulf due to the increase in heat flux during spring and summer. The water retained
from the previous winter forms a cold water mass below the thermocline [
31
,
32
]. Secondly,
a tidal front is formed between the mixing zone and the stratification zone in the middle of
the Beibu Gulf due to strong tidal mixing along the coastal area on the west side of Hainan
Island. The difference in pressure gradients on either side of the tidal front eventually
forms the W region [
33
–
35
]. Therefore, the causes of the upwellings along the coast of
Hainan Island are significantly different, with the eastern and northeastern upwelling
mainly related to the monsoon and the W region mainly related to the summer stratification
and the tidal front in the Beibu Gulf. Thus, the northwestern SCS is an ideal area to carry
out a systematic study about the impact of heatwaves on upwelling.
Here, we integrate satellite and reanalysis daily data from 1998 to 2021 to investigate
the factors influencing the changes in upwelling associated with different causal mecha-
nisms during the AMHW events, considering both the temporal and spatial distributions of
synthetic event sequences. Furthermore, we quantify their contributions to the variations
in upwelling during different phases of the AMHW, aiming to elucidate the impact of the
AMHW on upwelling driven by various causal mechanisms.
Remote Sens. 2024,16, 131 3 of 20
Remote Sens. 2024, 16, x FOR PEER REVIEW 3 of 21
Figure 1. Location and Topography of the Study Area (a), Spatial Distribution of SummerAveraged
SST (b), Mean Wind Speed and Ekman Pumping Velocity (c) over Multiple Years (1982–2021). In
(b), the pink parallelograms represent the core regions of upwelling, the black rectangles represent
the areas potentially affected by upwelling, and the blue rectangles represent the non-upwelling
areas (with the exceptions of the black rectangles). NE region represents 19.6–21.5°N, 109.8–112.4°E;
E region represents 17.9–19.6°N, 109.7–112.1°E; and W region represents 17.5–20.1°N, 107.2–109.5°E.
In (c), positive velocity means upwelling.
Here, we integrate satellite and reanalysis daily data from 1998 to 2021 to investigate
the factors influencing the changes in upwelling associated with different causal mecha-
nisms during the AMHW events, considering both the temporal and spatial distributions
of synthetic event sequences. Furthermore, we quantify their contributions to the varia-
tions in upwelling during different phases of the AMHW, aiming to elucidate the impact
of the AMHW on upwelling driven by various causal mechanisms.
2. Data and Methods
2.1. Data Sources
The intensity of MHW [36] can be derived from SST obtained from the OSTIA (an
operation, real-time, high-resolution, global SST analysis system, hps://data.marine.co-
pernicus.eu/product/SST_GLO_SST_L4_REP_OBSERVATIONS_010_011; accessed on 1
July 2023) daily SST images with a 0.05° × 0.05° resolution [37]. ERA5 is a global climate
atmospheric reanalysis produced by the European Centre for Medium-Range Weather
Forecasts [38], which is the fifth generation in the series (hps://cds.climate.coperni-
cus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means; accessed on 1 July
2023). This reanalysis provides hourly estimates of various atmospheric, land, and oceanic
variables from 1979 to 2023. The present study utilizes several key variables, including
daily mean net surface solar radiation, 10 m wind speeds as well as mean sea level pres-
sure. The spatial resolution of the dataset is 0.25 degrees. The Chl-a daily L4 dataset, cov-
ering the time period from 1997 to 2022, was obtained from the Global Ocean Color
Figure 1. Location and Topography of the Study Area (a), Spatial Distribution of SummerAveraged
SST (b), Mean Wind Speed and Ekman Pumping Velocity (c) over Multiple Years (1982–2021). In (b),
the pink parallelograms represent the core regions of upwelling, the black rectangles represent the
areas potentially affected by upwelling, and the blue rectangles represent the non-upwelling areas
(with the exceptions of the black rectangles). NE region represents 19.6–21.5
◦
N, 109.8–112.4
◦
E; E
region represents 17.9–19.6
◦
N, 109.7–112.1
◦
E; and W region represents 17.5–20.1
◦
N, 107.2–109.5
◦
E. In
(c), positive velocity means upwelling.
2. Data and Methods
2.1. Data Sources
The intensity of MHW [
36
] can be derived from SST obtained from the OSTIA (an
operation, real-time, high-resolution, global SST analysis system, https://data.marine.
copernicus.eu/product/SST_GLO_SST_L4_REP_OBSERVATIONS_010_011; accessed on
1 July 2023) daily SST images with a 0.05
◦×
0.05
◦
resolution [
37
]. ERA5 is a global climate
atmospheric reanalysis produced by the European Centre for Medium-Range Weather
Forecasts [
38
], which is the fifth generation in the series (https://cds.climate.copernicus.
eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means; accessed on 1 July
2023). This reanalysis provides hourly estimates of various atmospheric, land, and oceanic
variables from 1979 to 2023. The present study utilizes several key variables, including
daily mean net surface solar radiation, 10 m wind speeds as well as mean sea level pressure.
The spatial resolution of the dataset is 0.25 degrees. The Chl-adaily L4 dataset, covering
the time period from 1997 to 2022, was obtained from the Global Ocean Color (Copernicus
GlobColour) database (https://data.marine.copernicus.eu/product/OCEANCOLOUR_
GLO_BGC_L4_MY_009_104; accessed on 1 July 2023) with a spatial resolution of 4
×
4 km.
2.2. Method
In the context of oceanographic dynamics, Ekman transport is modulated by the inter-
active forces of wind stress and the Coriolis effect. This interaction fosters a convergence
Remote Sens. 2024,16, 131 4 of 20
and divergence in marine waters, subsequently exerting an impact on the velocity of Ekman
pumping (referred to as EPV) [39].
EPV =curlτ
ρf(1)
where
ρ
and frepresent the density of sea water and the Coriolis coefficient, respectively.
The coefficient can be quantified as 2
ω
sin
θ
, where
ω
symbolizes the Earth’s angular
velocity of rotation and
θ
embodies the geographical latitude.
→
T
is wind stress, which was
calculated as follows:
→
τ=ρa·Cd·
→
U
·→
U (2)
where
ρa
is the air density,
→
U
is the wind vector at 10 m above sea level, and
Cd
is the drag
coefficient, which was calculated as follows [40]:
Cd=
0.29 +3.1
|→
U|+7.2
|→
U|2×10−3, 3 ≤ |→
U| ≤ 6 m/s
(0.60 +0.071|→
U|)×10−3, 6 ≤ |→
U| ≤ 26 m/s
(3)
The wind curl was calculated using the wind stress:
curl →
τ=∂τx
∂y+∂τy
∂x(4)
In line with Hobday et al. [
36
], several tools have been developed to automatically
detect and provide statistical descriptions of MHW events [
41
]. In this study, we utilized the
MATLAB implementation developed by Zhao and Martin [
42
], which is publicly available
at https://github.com/ZijieZhaoMMHW/m_mhw1.0 (accessed on 1 March 2023). Detail
parameters for MHW detection followed Matlab tool defaults: spatial climatology and
threshold were calculated with a 5-day sliding window; MHW events were identified
using a 90th percentile threshold; spatial climatology and threshold smoothing employed a
31-day moving mean window; a minimum 5-day duration was required for MHW event
recognition, and a maximum 2-day gap was permitted for joining successive MHW events.
Tm(j) = ∑ye
y=ys∑j+5
d=j−5
T(y,d)
11(ye−ys+1)(5)
imean =T(t)−Tm(j)(6)
The climatological SST mean (
Tm
) used in this study was calculated from 1 January
1982 to 31 December 2011, and the daily SST on day dof year yis represented by T.
In order to investigate AMHW across the entire region rather than focusing on local-
ized small grid points [
43
], we selected mean SSTas the indicator for AMHW events. This
approach effectively eliminates small-scale ocean processes and enhances the discernibility
of larger-scale atmospheric influences on AMHW events. Additionally, the weakening
upwelling can also lead to MHW [
44
]. Thus, we excluded the upwelling areas (as shown
in black rectangles in Figure 1b) and retained only the SST from non-upwelling regions
surrounding them as indicators of AMHW events to avoid potential causal inversion re-
sulting from feedback processes. As the average duration of heatwaves in this study was
11 days, short-term surface heating in the upwelling regions would not significantly alter
the temperature at the bottom of the seawater [
45
]. Therefore, the difference between the
density derived from the SST and climatological mean salinity in the upwelling region and
the climatological density was utilized as an indicator of seawater stratification during the
AMHW event.
The extent of the upwelling is defined by the climatological mean SST, where the
general range of the upwelling is initially determined by isotherms (29
◦
C and 28.3
◦
C
Remote Sens. 2024,16, 131 5 of 20
isotherm for the west and east of Hainan Island, respectively). Subsequently, considering
the shape of the coastline and the isotherms, core regions representing the characteristics
of upwelling in different regions are further selected as the focus area of the study (as
shown in pink parallelograms in Figure 1b). Due to the larger extent of upwelling off
the eastern coast of Hainan Island, it is further divided into the eastern and northeastern
parts, respectively. To decouple the MHW events from upwelling events, the average
temperatures of the non-upwelling areas surrounding the upwelling areas are selected as
criteria for identifying AMHW occurrences (Figure 1b), because atmospheric high-pressure
systems typically influence the sea areas near the high-pressure centers. Accordingly, from
1998 to 2021, a total of 28, 30, and 31 independent AMHW events were identified in the
E, NE, and the upwelling in the WH (W) regions, respectively. Events in different regions
occasionally occur on the same date.
To better illustrate the inhibitory effect of AMHW on different upwelling regions,
Figure 2presents the spatially synthesized distribution of the periods before, during, and
the difference between the periods for each region. This is based on the average duration
of AMHW events and the changes of variables over time, as detailed in Figures 3and 4.
Pre-AMHW refers to the days in the E and NE regions that were influenced by AMHW
but did not exhibit significant warming, ranging from
−
10 to
−
6 days (with the day of
heatwave occurrence designated as 0). The time period affected by AMHW in the E and
NE is defined as during AMHW, ranging from
−
5 to +11 days. Compared to the E and NE
regions, the wind stress and Chl-ain the W region reach their peak values in a shorter time
before the maturation of AMHW (Figure 4a,c). Therefore, pre-AMHW in the W region is
defined as −5 to −1 days, and the AMHW period is defined as 0 to +11 days.
Remote Sens. 2024, 16, x FOR PEER REVIEW 5 of 21
the temperature at the boom of the seawater [45]. Therefore, the difference between the
density derived from the SST and climatological mean salinity in the upwelling region
and the climatological density was utilized as an indicator of seawater stratification dur-
ing the AMHW event.
The extent of the upwelling is defined by the climatological mean SST, where the
general range of the upwelling is initially determined by isotherms (29 °C and 28.3 °C
isotherm for the west and east of Hainan Island, respectively). Subsequently, considering
the shape of the coastline and the isotherms, core regions representing the characteristics
of upwelling in different regions are further selected as the focus area of the study (as
shown in pink parallelograms in Figure 1b). Due to the larger extent of upwelling off the
eastern coast of Hainan Island, it is further divided into the eastern and northeastern parts,
respectively. To decouple the MHW events from upwelling events, the average tempera-
tures of the non-upwelling areas surrounding the upwelling areas are selected as criteria
for identifying AMHW occurrences (Figure 1b), because atmospheric high-pressure sys-
tems typically influence the sea areas near the high-pressure centers. Accordingly, from
1998 to 2021, a total of 28, 30, and 31 independent AMHW events were identified in the E,
NE, and the upwelling in the WH (W) regions, respectively. Events in different regions
occasionally occur on the same date.
To beer illustrate the inhibitory effect of AMHW on different upwelling regions,
Figure 2 presents the spatially synthesized distribution of the periods before, during, and
the difference between the periods for each region. This is based on the average duration
of AMHW events and the changes of variables over time, as detailed in Figures 3 and 4.
Pre-AMHW refers to the days in the E and NE regions that were influenced by AMHW
but did not exhibit significant warming, ranging from −10 to −6 days (with the day of
heatwave occurrence designated as 0). The time period affected by AMHW in the E and
NE is defined as during AMHW, ranging from −5 to +11 days. Compared to the E and NE
regions, the wind stress and Chl-a in the W region reach their peak values in a shorter time
before the maturation of AMHW (Figure 4a,c). Therefore, pre-AMHW in the W region is
defined as −5 to −1 days, and the AMHW period is defined as 0 to +11 days.
Figure 2. Spatial Distributions of SST Anomalies in Three Upwelling Regions During Different Phases
of AMHW. Panels (a–c) show the difference (Delta) in SST anomalies, panels (d–f) illustrate SST
anomalies during AMHW, and panels (g–i) depict SST anomalies in the Pre-AMHW phase. Each
column corresponds to a specific region, with (a,d,g) for the E Region, panels (b,e,h) for the NE
Region, panels (c,f,i) for the W Region.
Remote Sens. 2024,16, 131 6 of 20
Remote Sens. 2024, 16, x FOR PEER REVIEW 6 of 21
Figure 2. Spatial Distributions of SST Anomalies in Three Upwelling Regions During Different
Phases of AMHW. Panels (a–c) show the difference (Delta) in SST anomalies, panels (d–f) illustrate
SST anomalies during AMHW, and panels (g–i) depict SST anomalies in the Pre-AMHW phase.
Each column corresponds to a specific region, with (a,d,g) for the E Region, panels (b,e,h) for the
NE Region, panels (c,f,i) for the W Region.
Figure 3. Variations in Relevant Indicators of Region E (blue curve) and Region NE (black curve)
during the 30 days before and after the occurrence of AMHW (synthetic average of all summer heat-
waves from 1998 to 2021). Day 0 represents the first day of heatwave occurrence. The blue region
represents the pre-AMHW phase, while the orange, red, and green regions represent the develop-
ment phase, mature phase, and decline phase of AMHW, respectively.
Figure 3. Variations in Relevant Indicators of Region E (blue curve) and Region NE (black curve)
during the 30 days before and after the occurrence of AMHW (synthetic average of all summer
heatwaves from 1998 to 2021). Day 0 represents the first day of heatwave occurrence. The blue region
represents the pre-AMHW phase, while the orange, red, and green regions represent the development
phase, mature phase, and decline phase of AMHW, respectively.
In addition, Pearson correlation coefficients were employed to analyze the relation-
ships, and the xcorr function in MATLAB 2021a was used to compute the normalized
cross-correlation coefficients between two vectors at all possible lags. To investigate the
patterns of short-term AMHW events, daily anomalies of all data from the summer seasons
of 1998–2021 were utilized to remove long-term trends and seasonal variations.
Remote Sens. 2024,16, 131 7 of 20
Remote Sens. 2024, 16, x. hps://doi.org/10.3390/xxxxx www.mdpi.com/journal/remotesensing
Figure 4. Variations in Relevant Indicators of Region W during the 30 days before and after the
occurrence of AMHW (synthetic average of all summer heatwaves from 1998 to 2021). Day 0 repre-
sents the rst day of heatwave occurrence. The blue region represents the pre-AMHW phase, while
the red and green regions represent the mature phase and decline phase of AMHW, respectively.
Figure 4. Variations in Relevant Indicators of Region W during the 30 days before and after the
occurrence of AMHW (synthetic average of all summer heatwaves from 1998 to 2021). Day 0
represents the first day of heatwave occurrence. The blue region represents the pre-AMHW phase,
while the red and green regions represent the mature phase and decline phase of AMHW, respectively.
3. Results
In the summer, influenced by the southwest monsoon (Figure 1c), wind-induced
upwelling occurs along the eastern coast of Hainan Island, where the SST in the upwelling
area is generally 1–2
◦
C lower than the surrounding waters. Similarly, upwelling is observed
in the W region, but it is generally weaker than the upwelling along the eastern coast of
Hainan Island, with a SST about 0.5–1
◦
C lower than the surrounding waters. During the
pre-AMHW, the SST climatic anomalies in E and NE regions are negative, indicating a
significant enhancement of upwelling (t-test, p< 0.001, Figure 2g–i). In contrast, there is
no significant enhancement of upwelling in the W region before the occurrence of AMHW.
During the AMHW events, the SST anomalies in the upwelling regions rapidly increased
and then slowly decreased (Figure 3e,f and Figure 4e,f). The spatial distribution of the
difference between AMHW and pre-AMHW periods varies significantly among the three
regions (Figure 2a–c). The SST differences between the AMHW period and the pre-AMHW
period exhibit notable spatial variations across different upwelling regions. For instance,
the SST differences in the E and NE during the AMHW period are predominantly localized
with local extreme values in their respective areas, while the difference in the W during
the AMHW period shows maximum values in the northwestern part of the study area.
This indicates the spatial heterogeneity of AMHW rather than synchronous warming in the
surrounding waters (Figure 2a–c).
Remote Sens. 2024,16, 131 8 of 20
From a temporal perspective, the period 5 days prior to the occurrence of a heatwave
is considered as the development phase of the associated AMHW. During this phase, SST
begins to show an increasing trend. From the day of heatwave occurrence and the following
4 days, the AMHW enters the mature phase, during which the intensity of the AMHW
rapidly increases and reaches its peak (Figure 3e). Subsequently, the AMHW enters the
decline phase, which is defined as the duration of AMHW events (11 days) minus the
duration of the mature phase (4 days). Due to the rapid development of heatwaves in the
W region, the wind speed starts to weaken only one or two days before the maturity of
the heatwave, and thus, the W region does not have a defined development phase. SST
continues to decrease for 1 to 2 weeks after the end of the heatwave until it reaches a steady
value similar to that before the occurrence of the heatwave. The climatic anomaly of SST
in the upwelling regions decreases to negative values before the occurrence of AMHW
(with a less noticeable decrease in the W region, approximately around 0.1
◦
C). However,
with the development of the heatwave, the SST increases to very high positive values
(Figures 3f and 4f). Due to the consistently positive climatological SST anomalies in the
non-upwelling area, the negative anomalies in the E and NE region are evidently caused
by the intensification of upwelling (Figure 3e,f). This indicates that before the development
phase of an AMHW, external conditions positively promote wind-driven upwelling, but as
the heatwave develops, the favorable external conditions for upwelling gradually diminish.
The upwelling regions exhibit weaker warming and slower cooling rates compared to the
non-upwelling regions, reflecting the inhibitory effect of upwelling on the AMHW and
the stability of SST in the upwelling regions. During the maturation of AMHW, there are
often several consecutive days of high-pressure weather, characterized by weak winds,
few clouds, and strong shortwave radiation (Figure 3c–e). In the NE and E regions, wind
stress is positively correlated with wind stress curl, while in the W region, wind stress
is negatively correlated with wind stress curl (Figure 3c,d and Figure 4c,d). Therefore,
during the period of an AMHW, the Ekman pumping effect may have an opposite impact
on upwelling.
Notably, during an AMHW event and a subsequent period (
−
5 to +30), the concentra-
tions of Chl-ain the three upwelling regions generally exhibit a High–Low–High trend. The
low values are generally negative, and the duration encompasses the entire AMHW phase
(Figures 3a and 4a). During the pre-AMHW period, Chl-aexhibits predominantly positive
anomalies, indicating the strengthening of upwelling. Following the decline of the AMHW,
it takes approximately two weeks for Chl-ato gradually return to the climatological mean,
highlighting the sustained impact of the brief AMHW event on upwelling.
To further investigate the inhibitory effects of AMHW on upwelling intensity and the
ecosystem, the correlation plots of various variables during the 11 days before and after the
occurrence of AMHW were conducted in this study (Figure 5). As heatwaves are short-term
events and may occur multiple times within a period, we focused on discussing the data
in the immediate vicinity of the heatwave occurrence as its influence. The concentrations
of Chl-ain all three regions showed a strong relationship with stratification intensity
(
|r| > 0.7
,p< 0.05), indicating the significant impact of stratification on upwelling during
heatwave events. In the NE region, there is a close correlation among Chl-a, stratification
intensity, and wind stress, with correlation coefficients exceeding 0.7 (p< 0.05), reflecting
the strongest influence of heatwaves on the NE upwelling region. The cross-correlation
coefficient between wind stress and Chl-ain the E region has a time lag; as the time
lag increased to the fourth day, the cross-correlation coefficient between them increased
from near 0 to a peak value of 0.6 (Figure 6). Finally, to quantify the effects of wind
stress reduction and stratification intensification (the two main processes of AMHW) on
the concentrations of Chl-a, the delayed Chl-aconcentration was subjected to correlation
analyses with both wind stress and stratification intensity. It was found that Chl-ashowed
a clear linear relationship with wind stress and stratification intensity during the AMHW
period. In the E region, the two sets of linear relationships have R
2
values of 0.47 and 0.52,
Remote Sens. 2024,16, 131 9 of 20
respectively, in the NE region; R
2
values are 0.51 and 0.66, and in the W region, R
2
values
are 0.37 and 0.56 (all p-values < 0.05, Figure 7).
Remote Sens. 2024, 16, x FOR PEER REVIEW 9 of 21
concentrations of Chl-a, the delayed Chl-a concentration was subjected to correlation anal-
yses with both wind stress and stratification intensity. It was found that Chl-a showed a
clear linear relationship with wind stress and stratification intensity during the AMHW
period. In the E region, the two sets of linear relationships have R2 values of 0.47 and 0.52,
respectively, in the NE region; R2 values are 0.51 and 0.66, and in the W region, R2 values
are 0.37 and 0.56 (all p-values < 0.05, Figure 7).
Figure 5. Correlation Analysis of Composite Heatwave Sequences for the 11 Days Before and After
the First Day of AMHW Occurrence. Panels (a–c) represent Regions E, NE, and W, respectively. The
Figure 5. Correlation Analysis of Composite Heatwave Sequences for the 11 Days Before and After
the First Day of AMHW Occurrence. Panels (a–c) represent Regions E, NE, and W, respectively. The
composite heatwave sequences are derived from the composite average of all summer heatwaves
from 1998 to 2021.
Remote Sens. 2024,16, 131 10 of 20
Remote Sens. 2024, 16, x FOR PEER REVIEW 10 of 21
composite heatwave sequences are derived from the composite average of all summer heatwaves
from 1998 to 2021.
Figure 6. Lagged Correlation Analysis of Various Indicators with Chl-a in Regions E (blue), NE
(black), and W (red). The time series indicators are derived from the synthetic heatwave sequence,
with a consistent length of 23 days, as described in Figure 5.
Figure 6. Lagged Correlation Analysis of Various Indicators with Chl-ain Regions E (blue), NE
(black), and W (red). The time series indicators are derived from the synthetic heatwave sequence,
with a consistent length of 23 days, as described in Figure 5.
Remote Sens. 2024, 16, x FOR PEER REVIEW 2 of 2
Figure 7. Detailed Linear Regression Analysis of Chl-a with Wind Stress and Stratication Intensity
in Regions E, NE, and W. Panels (a,d,g) display multiple linear regression of Chl-a against wind
stress and stratication. Panels (b,e,h) illustrate simple linear regression of Chl-a against wind
stress, while panels (c,f,i) present simple linear regression of Chl-a against stratication. The red
dots in panels (a,d,g) represent data points outside the 95% condence interval.
Figure 7. Detailed Linear Regression Analysis of Chl-awith Wind Stress and Stratification Intensity
in Regions E, NE, and W. Panels (a,d,g) display multiple linear regression of Chl-aagainst wind stress
and stratification. Panels (b,e,h) illustrate simple linear regression of Chl-aagainst wind stress, while
panels (c,f,i) present simple linear regression of Chl-aagainst stratification. The red dots in panels
(a,d,g) represent data points outside the 95% confidence interval.
Remote Sens. 2024,16, 131 11 of 20
4. Discussion
4.1. Wind Weakening and Stratification Enhancing during AMHW Events
The occurrence of AMHW can be mainly attributed to strong weather patterns, such as
persistent high-pressure systems and atmospheric blocking, as well as reduced cloud cover
and precipitation [
12
,
46
–
48
]. The Western North Pacific Subtropical High is the dominant
circulation system in the summer climate of the Western Pacific [
49
], and the anomalies
of the Western North Pacific Subtropical High can cause abnormal monsoon patterns
and various extreme weather events in the Western Pacific, including the northwestern
SCS [
50
–
53
]. In this study, under the influence of the Western North Pacific Subtropical
High, the frequent conditions of clear sky, low cloud cover, and weak wind lead to a
significant increase in surface shortwave radiation [
54
,
55
]. This hot and dry weather
provides favorable conditions for the occurrence of AMHW.
Since the average duration of a heatwave is approximately 11.1 days, we conducted
a correlation analysis of the variables by examining the changes in each variable during
the 12 days before and after the maturity of AMHW (referred to as day 0). The results are
shown in Figures 5and 6. The sea-level atmospheric pressure reaches its peak at around
−
2 to
−
1 days before the maturation of AMHW. During the pre-AMHW period, the wind
stress in the three upwelling regions initially increases to a positive climatic anomaly and
then decreases continuously until reaching its lowest value 2–3 days after the peak of
sea-level atmospheric pressure (Figures 3and 4c,d,h). Due to the higher terrain of Hainan
Island, the south winds blowing over Hainan Island generate a positive wind stress curl
on the eastern side and a negative wind stress curl on the western side (Figure 1c). Both
wind stress curls in the NE and E regions positively correlate with the change in wind
stress, with correlation coefficients of 0.84 and 0.91, respectively (both p< 0.05). In the W
region, however, the wind stress curl changes negatively correlated with wind stress, with a
correlation coefficient of
−
0.50 (p< 0.05). Furthermore, these findings, however, introduce
concerns of collinearity due to the synchronized changes in both factors, thus complicating
the isolation of their individual contributions to the weakening of the upwelling. To resolve
this, the wind’s influence in the subsequent discussion is represented solely by wind stress
magnitude. It should be noted, though, that this discussion inherently includes the effects
of both Ekman transport and Ekman pumping on upwelling.
In addition, the anticyclonic center (high-pressure center) of low wind speed before
the occurrence of the AMHW is mostly located on the eastern side of the corresponding
upwelling regions (Figure 8g–i). Although the high-pressure center does not appear in
the pre-AMHW period of the NE region, it can be inferred to be on the eastern side of
the study area according to the wind rotation (Figure 8g–i). As the heatwave develops,
the high-pressure center starts to extend westward, consistent with the variations of the
Northwestern Subtropical High [
56
]. This keeps the upwelling regions in a state of weak
winds until the high-pressure center moves away. During the AMHW period, the climatic
anomaly of surface net shortwave radiation also shows an increasing and then decreasing
trend, reaching its highest value of 0.01 J/m
2
at +1 day (Figures 3g and 4g). This trend is
similar to the change in wind stress and lags behind the atmospheric pressure change by
2–3 days. The density difference representing the stratification effect reaches its maximum
value of approximately 0.2 kg/m3at +3 days (Figures 3b and 4b).
4.2. The Inhibitory Effects of AMHW on Upwelling
The SST difference and temperature point index (TPI) are widely used as indicators
for the intensity of coastal upwelling [
57
–
60
]. However, due to the inhibitory effect of
upwelling on rapid warming and heatwave occurrences [
13
,
14
,
61
], the SST difference
and TPI value in the upwelling regions tend to be amplified, resulting in false signals of
Remote Sens. 2024,16, 131 12 of 20
enhanced upwelling. Wind stress is considered another important indicator for the intensity
of coastal upwelling, such as the Bakun Index. This index utilizes the coastal component
of wind stress to estimate nearshore Ekman transport [
62
,
63
]. However, the Bakun Index
does not represent the variations of oceanic conditions during the wind-driven upwelling
events. Moreover, the variation in the oceanic stratification effect becomes significant
when SST increases rapidly during AMHW. Therefore, additional indicators are needed to
characterize the changes in upwelling during AMHW. Upwelling can transport nutrients
from the deeper water to the surface [
64
]. A short-term variation in Chl-aassociated with
coastal upwelling also shows that phytoplankton growth is approximately 2 days later
than upwelling activity [
65
,
66
]. Thus, the variation in Chl-aresulting from upwelling can
effectively reflect the influence of stratification and wind on upwelling.
Remote Sens. 2024, 16, x FOR PEER REVIEW 12 of 21
on the eastern side and a negative wind stress curl on the western side (Figure 1c). Both
wind stress curls in the NE and E regions positively correlate with the change in wind
stress, with correlation coefficients of 0.84 and 0.91, respectively (both p < 0.05). In the W
region, however, the wind stress curl changes negatively correlated with wind stress, with
a correlation coefficient of −0.50 (p < 0.05). Furthermore, these findings, however, intro-
duce concerns of collinearity due to the synchronized changes in both factors, thus com-
plicating the isolation of their individual contributions to the weakening of the upwelling.
To resolve this, the wind’s influence in the subsequent discussion is represented solely by
wind stress magnitude. It should be noted, though, that this discussion inherently in-
cludes the effects of both Ekman transport and Ekman pumping on upwelling.
In addition, the anticyclonic center (high-pressure center) of low wind speed before
the occurrence of the AMHW is mostly located on the eastern side of the corresponding
upwelling regions (Figure 8g–i). Although the high-pressure center does not appear in the
pre-AMHW period of the NE region, it can be inferred to be on the eastern side of the
study area according to the wind rotation (Figure 8g–i). As the heatwave develops, the
high-pressure center starts to extend westward, consistent with the variations of the
Northwestern Subtropical High [56]. This keeps the upwelling regions in a state of weak
winds until the high-pressure center moves away. During the AMHW period, the climatic
anomaly of surface net shortwave radiation also shows an increasing and then decreasing
trend, reaching its highest value of 0.01 J/m2 at +1 day (Figures 3g and 4g). This trend is
similar to the change in wind stress and lags behind the atmospheric pressure change by
2–3 days. The density difference representing the stratification effect reaches its maximum
value of approximately 0.2 kg/m3 at +3 days (Figures 3b and 4b).
Figure 8. Spatial Distributions of Wind Vector Anomalies and Wind Anomalies in Three Upwelling
Regions During Different Phases of AMHW. Panels (a–c) depict the Delta (During-Pre), panels (d–
f) the AMHW period, and panels (g–i) the Pre-AMHW phase, each showcasing wind vector anom-
alies and wind anomalies. Each column corresponds to a specific region, with (a,d,g) for the E Re-
gion, panels (b,e,h) for the NE Region, panels (c,f,i) for the W Region.
Figure 8. Spatial Distributions of Wind Vector Anomalies and Wind Anomalies in Three Upwelling
Regions During Different Phases of AMHW. Panels (a–c) depict the Delta (During-Pre), panels
(d–f) the AMHW period, and panels (g–i) the Pre-AMHW phase, each showcasing wind vector
anomalies and wind anomalies. Each column corresponds to a specific region, with (a,d,g) for the E
Region, panels (b,e,h) for the NE Region, panels (c,f,i) for the W Region.
Due to the different coastlines, the upwelling in the E and NE regions is generated
by southwest and southeast winds, respectively [
67
], whereas the W region experiences a
combination of tidal-induced upwelling and wind-induced downwelling [
35
]. In this study,
the three upwelling regions undergo changes with variations in the wind field during
AMHW (Figures 8and 9). Prior to AMHW maturation, the climatological anomalies in
wind speed in the E and NE regions are positive; and the climatological anomalies of wind
vectors are southeasterly and southerly winds, both conducive to upwelling. Accordingly,
the climatological anomalies of Chl-ain these two regions significantly increase (Figures
8g and 9f–h). In the mature phase of AMHW events in the E and NE regions, there is a
significant change in the wind vector anomalies compared to the pre-AMHW conditions.
The anomalies in the NE region shift to northwesterly winds, while the anomalies in the E
region shift to northeasterly winds, which are unfavorable for upwelling and result in a
significant reduction in Chl-aat the corresponding locations (Figure 8a,b and Figure 9a,b).
Remote Sens. 2024,16, 131 13 of 20
Remote Sens. 2024, 16, x FOR PEER REVIEW 13 of 21
4.2. The Inhibitory Effects of AMHW on Upwelling
The SST difference and temperature point index (TPI) are widely used as indicators
for the intensity of coastal upwelling [57–60]. However, due to the inhibitory effect of
upwelling on rapid warming and heatwave occurrences [13,14,61], the SST difference and
TPI value in the upwelling regions tend to be amplified, resulting in false signals of en-
hanced upwelling. Wind stress is considered another important indicator for the intensity
of coastal upwelling, such as the Bakun Index. This index utilizes the coastal component
of wind stress to estimate nearshore Ekman transport [62,63]. However, the Bakun Index
does not represent the variations of oceanic conditions during the wind-driven upwelling
events. Moreover, the variation in the oceanic stratification effect becomes significant
when SST increases rapidly during AMHW. Therefore, additional indicators are needed
to characterize the changes in upwelling during AMHW. Upwelling can transport nutri-
ents from the deeper water to the surface [64]. A short-term variation in Chl-a associated
with coastal upwelling also shows that phytoplankton growth is approximately 2 days
later than upwelling activity [65,66]. Thus, the variation in Chl-a resulting from upwelling
can effectively reflect the influence of stratification and wind on upwelling.
Due to the different coastlines, the upwelling in the E and NE regions is generated
by southwest and southeast winds, respectively [67], whereas the W region experiences a
combination of tidal-induced upwelling and wind-induced downwelling [35]. In this
study, the three upwelling regions undergo changes with variations in the wind field dur-
ing AMHW (Figures 8 and 9). Prior to AMHW maturation, the climatological anomalies
in wind speed in the E and NE regions are positive; and the climatological anomalies of
wind vectors are southeasterly and southerly winds, both conducive to upwelling. Ac-
cordingly, the climatological anomalies of Chl-a in these two regions significantly increase
(Figures 8g and 9f–h). In the mature phase of AMHW events in the E and NE regions,
there is a significant change in the wind vector anomalies compared to the pre-AMHW
conditions. The anomalies in the NE region shift to northwesterly winds, while the anom-
alies in the E region shift to northeasterly winds, which are unfavorable for upwelling and
result in a significant reduction in Chl-a at the corresponding locations (Figures 8a,b and
9a,b).
Figure 9. Spatial Distributions of Chl-aAnomalies in Three Upwelling Regions During Different
Phases of AMHW. Panels (a–c) depict the Delta (During-Pre), panels (d–f) the AMHW period, and
panels (g–i) the Pre-AMHW phase, each showcasing Chl-a. Each column corresponds to a specific
region, with (a,d,g) for the E Region, panels (b,e,h) for the NE Region, panels (c,f,i) for the W Region.
It is worth noting that the weakening of upwelling in the NE region during an AMHW
events is more pronounced than in the E region (Figure 3a), and this may be attributed to
multiple factors. Firstly, following the weakening of the generating variables, namely wind,
the stronger pre-existing upwelling in the NE region compared to the E region (Figure 1b)
may render it more susceptible to suppression. Secondly, the NE region exhibits stronger
vertical turbulent mixing that aids in the upward transport of water [
23
], and numerical
studies by Bai et al. also revealed that local intense mixing favors the growth of upwelling in
the NE region [
68
]. Therefore, when the wind, which plays a crucial role in promoting mixing,
weakens, the weakening of upwelling in the NE region becomes more pronounced. Lastly,
the coupling between the coastal upwelling direction and the trajectory of the high-pressure
system movement is likely a key influencing factor in determining the magnitude of upwelling
weakening during AMHW events. Previous studies have indicated that the subtropical high-
pressure system in the northwestern Pacific is located around 20
◦
N and develops from
southeast to northwest, often traversing the study area [
54
,
69
,
70
]. As mentioned earlier, for
an AMHW event to occur near the wind-driven upwelling region, the wind anomalies often
point in an unfavorable direction. Therefore, the presence of the anticyclonic high-pressure
center triggering the corresponding AMHW event in the E region requires it to be positioned
in the northwest of the E region (Figure 8d). Similarly, for an AMHW event in the NE region,
with anomalous northwesterly winds prevailing, the high-pressure center needs to appear in
the southwest of the NE region (Figure 8e). Thirdly, due to the trajectory of the high-pressure
center moving from southeast to northwest through the study area, the high-pressure center
triggering AMHW events in the NE region can only appear near Hainan Island, while the
high-pressure center inducing AMHW events in the E region is more likely to be located far
from Hainan Island and on the northern side of the Beibu Gulf (Figure 8d,e). Consequently,
the upwelling in the NE region, which is in closer proximity to the high-pressure center during
the AMHW period, experiences lower wind speeds.
Remote Sens. 2024,16, 131 14 of 20
Surprisingly, in the W region, the climatological wind direction anomalies of coastal wind
vectors during Delta AMHW are favorable for upwelling, but the Chl-adoes not increase
(Figures 8c and 9c). First, the cause may be that during pre-AMHW, the wind vectors are
precisely eastward and horizontal to the mouth of the Beibu Gulf, causing a large amount
of water to accumulate within the bay (Figure 8i). The nutrients transported by the Western
Guangdong coastal current are mostly confined to the northern bay, resulting in widespread
phytoplankton blooms along the entire coastal area of western Hainan Island and positive Chl-a
anomalies within the Beibu Gulf (Figure 9i) [
64
,
71
]. During AMHW, however, the wind vector
anomalies are southward, perpendicular to the mouth of the Beibu Gulf, and the wind no longer
promotes water accumulation. As a result, the Chl-ain the W region decreases despite the
favorable wind conditions for upwelling. Secondly, as wave mixing enhanced by increased
wind speed promotes the intensity of W region upwelling [
34
], the reduced wind speed during
AMHW leads to a weaker upwelling intensity in the W region. This positive correlation between
wind and upwelling in the W region is directly illustrated in Figure 6a.
In addition, stratification is an important influencing factor that alters the intensity of
upwelling. The depth of the upwelling source is closely related to its strength and decreases
with increasing stratification [
72
,
73
]. Similarly, the fishery resources in the upwelling ecosystems
also decrease with increasing stratification [
74
]. Strong correlations between the sea surface
stratification and Chl-acan be observed, reaching
−
0.84,
−
0.81, and
−
0.72 in the E, NE, and
W regions, respectively (Figure 5). Additionally, both stratification indices and MHW intensity
are closely related to temperature, exhibiting consistent and strong correlations of above 0.85
(Figure 5). This suggests that MHW intensity is essentially a measure of temperature stratification
and is also influenced by atmospheric forcing, albeit with a lag compared to the latter.
As previously mentioned, during AMHW, the NE region exhibits the smallest Chl-a
concentration, indicating the strongest inhibition by AMHW, followed by the W region, and
the E region with the lowest inhibition. The higher correlation between upwelling in the NE
region and both stratification and wind, along with the greater magnitude of wind stress
weakening and stratification enhancement in the NE region, can also explain this phenomenon
(Figure 3b,c, Figure 4b,c and Figure 5b). In contrast, despite experiencing the largest reduction
in wind stress, the decrease in Chl-aconcentration in the W region is limited (Figure 4a,c),
primarily due to its tidal origin rather than wind-driven processes. Cross-correlation results
between stratification intensity and Chl-ademonstrate that the variations in Chl-ain all three
regions lag behind stratification by approximately 1 day (Figure 6d). The minimum values
of Chl-aoccur between +1 and +8 days. The changes in Chl-aduring AMHW in the three
upwelling regions lag behind wind stress by approximately 1–6 days (Figures 4and 5a,c),
which is consistent with the cross-correlation results between Chl-aand wind stress and wind
stress curl (Figure 6c,d). However, in the NE and W regions, the cross-correlation coefficients
between Chl-aand wind stress and wind stress curl reach their maximum values at lag days
of 0–1, indicating almost no lag effect. Thus, similar to the W region, the NE region may be
influenced by the Western Guangdong coastal current [64,71,75].
4.3. The Contributions of Stratification Enhancement and Wind Weakening to the Decrease in
Chl-a Concentration during Different Phases of AMHW
Due to the lagged days between Chl-aand wind stress during AMHW (4, 0, and 1 for
the E, NE, and W regions, respectively), linear regression analyses were performed between
the Chl-aseries lagged by the corresponding days and wind stress and stratification inten-
sity. Strong linear relationships were observed in all three regions (Figure 7). Particularly,
after conducting bivariate linear regression, the R
2
values for the linear functions between
Chl-aand these two factors reached 0.7, 0.68, and 0.58 for the E, NE, and W regions, re-
spectively. The coefficients of the stratification component in the bivariate regression were
−
0.37,
−
0.78, and
−
0.64 for the E, NE, and W regions, respectively, indicating that the NE
region is mostly influenced by stratification, followed by the W region, which is slightly less
influenced but still significantly more than the E region. The coefficients of the wind stress
component in the three regions were 5.3, 3.3, and 1.6, respectively. By combining these
Remote Sens. 2024,16, 131 15 of 20
coefficients, it can be concluded that the upwelling in the W region is more susceptible to
stratification, while the upwelling in the E region is more influenced by wind stress, and
the NE region is sensitive to changes in both processes.
Based on the results of bivariate linear regression, the contributions of wind weakening
and stratification strengthening in the three upwelling regions during different periods of
AMHW to the reduction in Chl-aor upwelling inhibition can be quantified. From the perspec-
tive of the total AMHW period, including the pre-AMHW phase, the absolute contributions of
wind weakening to the reduction in Chl-aconcentration are consistent for the E and NE regions.
On the other hand, the absolute contribution of stratification strengthening to the reduction in
Chl-aconcentration is approximately 1/5 higher for the NE region compared to the W region
and twice as high compared to the E region (Figure 10). In terms of the proportion between the
two contributions, the contribution of wind stress in the E region is twice as high as in the NE
regions. Thus, wind and stratification in the E and NE regions promote the development of
upwelling during the pre-AMHW phase. However, during the development phase, they shift
to inhibiting factors, with wind stress still playing a significant role. When AMHW reaches its
mature phase, the inhibitory effects of both factors are at their strongest. In the decline phase,
stratification mainly plays a role, as the wind field, which was initially favorable for AMHW,
has already returned to normal due to the movement and changes in the high-pressure center,
leaving only the heated SST to continue inhibiting upwelling.
Remote Sens. 2024, 16, x FOR PEER REVIEW 16 of 21
returned to normal due to the movement and changes in the high-pressure center, leaving
only the heated SST to continue inhibiting upwelling.
Figure 10. Contributions and Relative Percentages of Wind and Stratification Effects on Chl-a Var i -
ations in Three Upwelling Regions during Different Phases of AMHW. Blue represents the wind
stress component, and red represents the stratification component. There is not a development
phase and stress component in the W region; thus, the values are not shown.
4.4. The Impact of AMHW on Marine Ecosystems
During the summer AMHW in the northwestern SCS, three distinct upwelling are
inhibited to varying degrees through stratification enhancement and wind weakening
(Figure 11), with greater inhibition by the stronger AMHW intensity. Although, in some
regions, the pre-mature AMHW wind paerns are favorable for upwelling, the intensifi-
cation and prolonged duration of heatwaves are expected to further accelerate this trend
under global warming [27,76]. This will inevitably lead to a long-term weakening of
upwelling, causing a severe impact on ecosystems. Over the past decades, the reduction
in oceanic upwelling along the Iberian Peninsula coast has been driving ecosystems to-
wards an irreversible direction, characterized by an increased frequency of harmful algal
blooms and decreased sardine catches [77]. As a renowned fishing ground located in the
upwelling zone on the eastern side of Hainan Island, the Qinglan fishing ground exerts a
significant influence on the growth of phytoplankton and the distribution and abundance
of zooplankton [78]. The weakening of upwelling could significantly alter the continental
shelf ecosystem in the northwestern SCS [78–80]. The traditional view suggests that
upwelling regions serve as refuges for temporary climate change impacts on coral reefs in
the face of heatwave disturbances [81,82]. The northwestern Beibu Gulf and the eastern
Figure 10. Contributions and Relative Percentages of Wind and Stratification Effects on Chl-a
Variations in Three Upwelling Regions during Different Phases of AMHW. Blue represents the wind
stress component, and red represents the stratification component. There is not a development phase
and stress component in the W region; thus, the values are not shown.
Remote Sens. 2024,16, 131 16 of 20
4.4. The Impact of AMHW on Marine Ecosystems
During the summer AMHW in the northwestern SCS, three distinct upwelling are
inhibited to varying degrees through stratification enhancement and wind weakening
(
Figure 11
), with greater inhibition by the stronger AMHW intensity. Although, in some
regions, the pre-mature AMHW wind patterns are favorable for upwelling, the intensifi-
cation and prolonged duration of heatwaves are expected to further accelerate this trend
under global warming [
27
,
76
]. This will inevitably lead to a long-term weakening of up-
welling, causing a severe impact on ecosystems. Over the past decades, the reduction in
oceanic upwelling along the Iberian Peninsula coast has been driving ecosystems towards
an irreversible direction, characterized by an increased frequency of harmful algal blooms
and decreased sardine catches [
77
]. As a renowned fishing ground located in the upwelling
zone on the eastern side of Hainan Island, the Qinglan fishing ground exerts a significant
influence on the growth of phytoplankton and the distribution and abundance of zoo-
plankton [
78
]. The weakening of upwelling could significantly alter the continental shelf
ecosystem in the northwestern SCS [
78
–
80
]. The traditional view suggests that upwelling
regions serve as refuges for temporary climate change impacts on coral reefs in the face
of heatwave disturbances [
81
,
82
]. The northwestern Beibu Gulf and the eastern coast of
Hainan Island are both rich in coral reef resources [
42
,
83
]. However, as offshore upwelling
weakens in the future, these coral reefs will face increasingly challenging conditions.
Remote Sens. 2024, 16, x FOR PEER REVIEW 17 of 21
coast of Hainan Island are both rich in coral reef resources [42,83]. However, as offshore
upwelling weakens in the future, these coral reefs will face increasingly challenging con-
ditions.
Figure 11. The diagram of AMHW-induced Suppression of Three Distinct Upwelling Systems.
5. Conclusions
Based on satellite remote sensing data, this study analyzes the synthetic sequence of
AMHW events (30 days before and after the occurrence of heatwaves) in three different
upwelling regions in the northwest SCS from 1998 to 2021. Two prominent features during
AMHW, namely, wind stress reduction and stratification intensification, significantly sup-
pressed the intensity of upwelling in those regions. During AMHW, all three upwelling
regions were inhibited by enhanced seawater stratification. By contrast, the upwelling in
the W region is inhibited by enhanced seawater stratification. The upwelling in both the
E and NE regions is wind-driven, regulated by both wind and stratification simultane-
ously. However, due to the combined influence of multiple factors, the NE region experi-
ences a greater reduction in upwelling compared to the E region. The causes could be the
following: (1) the background upwelling in the NE region is stronger than in the E; (2)
Mixing triggered by wind exhibits a stronger promoting effect; (3) The coastline of the
upwelling region, in conjunction with the movement trajectory of the high-pressure sys-
tem, determines the location of the high-pressure center during the occurrence of AMHW.
Specifically, during the NE region’s AMHW period, the high-pressure center is positioned
in closer proximity to the upwelling area. To quantify the contributions of wind stress and
stratification changes during AMHW to the variations in upwelling, linear fits were per-
formed between Chl-a and wind stress and stratification intensity. It was found that dur-
ing the total period in all regions, stratification had an overwhelmingly dominant inhibi-
tory effect on Chl-a, but the contribution of wind stress was much stronger in the E region.
During the pre-AMHW period, both wind and stratification factors positively promote
wind-driven upwelling in the E and NE regions. However, as AMHW develops, the pro-
moting effect transitions into an inhibiting effect. The three upwelling regions experience
the maximum inhibition during the mature phase. After entering the decline phase, the
influence of wind stress becomes negligible, and the inhibition of Chl-a concentration is
primarily aributed to stratification effects.
Figure 11. The diagram of AMHW-induced Suppression of Three Distinct Upwelling Systems.
5. Conclusions
Based on satellite remote sensing data, this study analyzes the synthetic sequence of
AMHW events (30 days before and after the occurrence of heatwaves) in three different
upwelling regions in the northwest SCS from 1998 to 2021. Two prominent features
during AMHW, namely, wind stress reduction and stratification intensification, significantly
suppressed the intensity of upwelling in those regions. During AMHW, all three upwelling
regions were inhibited by enhanced seawater stratification. By contrast, the upwelling in
the W region is inhibited by enhanced seawater stratification. The upwelling in both the E
and NE regions is wind-driven, regulated by both wind and stratification simultaneously.
However, due to the combined influence of multiple factors, the NE region experiences a
greater reduction in upwelling compared to the E region. The causes could be the following:
(1) the background upwelling in the NE region is stronger than in the E; (2) Mixing triggered
by wind exhibits a stronger promoting effect; (3) The coastline of the upwelling region,
Remote Sens. 2024,16, 131 17 of 20
in conjunction with the movement trajectory of the high-pressure system, determines the
location of the high-pressure center during the occurrence of AMHW. Specifically, during
the NE region’s AMHW period, the high-pressure center is positioned in closer proximity to
the upwelling area. To quantify the contributions of wind stress and stratification changes
during AMHW to the variations in upwelling, linear fits were performed between Chl-a
and wind stress and stratification intensity. It was found that during the total period in all
regions, stratification had an overwhelmingly dominant inhibitory effect on Chl-a, but the
contribution of wind stress was much stronger in the E region. During the pre-AMHW
period, both wind and stratification factors positively promote wind-driven upwelling in
the E and NE regions. However, as AMHW develops, the promoting effect transitions
into an inhibiting effect. The three upwelling regions experience the maximum inhibition
during the mature phase. After entering the decline phase, the influence of wind stress
becomes negligible, and the inhibition of Chl-aconcentration is primarily attributed to
stratification effects.
Author Contributions: Conceptualization, S.L., Q.L. and F.C.; Methodology, S.L.; Software, S.L.;
Validation, F.C.; Formal analysis, S.L. and Q.L.; Resources, F.C.; Data curation, S.L.; Writing—original
draft, S.L. and Q.L.; Writing—review & editing, S.L., Q.L., X.Z., G.J., C.C. and F.C.; Visualization, S.L.;
Supervision, F.C.; Project administration, F.C.; Funding acquisition, F.C. All authors have read and
agreed to the published version of the manuscript.
Funding: This study was supported by the National Natural Science Foundation of China (U1901213,
92158201, 42276047), Entrepreneurship Project of Shantou (2021112176541391), Scientific Research
Start-Up Foundation of Shantou University (NTF20006), and Guangdong Provincial College Innova-
tion Team Project (2019KCXTF021).
Data Availability Statement: Data are contained within the article.
Conflicts of Interest: The authors declare no conflict of interest.
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